Because of system size, technology, and cost constraints, automotive radar sensors may have performance limitations with regard to discriminating two objects that have similar position and Doppler shift characteristics, or if one object has a substantially larger Radar Cross Section (RCS) than a second nearby object. Examples of two objects with similar range and Doppler shift reflection characteristics that typical automotive radar systems have difficulty discerning include: a slowly moving pedestrian walking around stationary or slowly moving passenger vehicle, a motor cycle traveling beside a tractor-trailer traveling in an adjacent lane at a similar range and range rate, and two passenger cars moving close to each other on adjacent lanes with similar range rates.
Automotive radar is used as a sensor for partially automated or fully autonomous operation of vehicles. Depending on angular-resolution requirements of these features, a wide-beam, or relatively narrow-beam transmit and receive antenna(s) or antenna-array(s) may be used, depending on the selected scanning concept (i.e. mechanical or electronics) across a given field-of-view. The transmit antenna radiates Radio Frequency (RF) signal that propagates toward an object in the radar field-of-view. The radio frequency signal is typically a pulse compressed waveform such as a series of waveform pulses commonly called ‘chirps’ or Frequency Modulated Continuous Wave, Pulse-Doppler and Frequency Shift Key. The signals reflected by the object depend on a backscatter property (i.e. Radar Cross Section) of the object. The signals reflected by the object are received by receiving antenna-array elements, which are typically connected to single (i.e. time-multiplexed) or multiple (i.e. not time-multiplexed) signal conditioning and processing devices. Depending on the selected receiver techniques (i.e. homodyne or heterodyne), the received RF-signal is converted to discreet baseband signal during propagation through signal conditioning devices chain. For a series of waveform pulses, the baseband signal is transferred from the base time-domain to a Range-Doppler frequency domain by a digital signal processing (or DSP) device, as will be recognized by those in the art. The amplitude of Range-Doppler spectrums from all of the receive antenna-array elements are averaged (i.e. non-coherently integrated). Prior automotive radar systems use this non-coherently integrated amplitude spectral profile as the basis for an object detection schema, i.e. a NCI-detection schema. The systems determine the NCI-spectrums for position and Doppler parameter estimation of detected objects which are characterized by a spectral-amplitude greater than a predetermined detection threshold. The NCI-detection technique is advantageous as it suppresses system noise variance, so keeps noise caused false-alarm rates to a minimum. The NCI-detection technique provides a net Signal-to-Noise Ratio (SNR) gain as system noise is less correlated across the antenna-array elements compared to the object reflected signal. Detected objects or targets are then selected for tracking. The tracker applies various tracking algorithms to evaluate and weight any time-dependent quantitative behaviors of object parameters to make a reliable determination for object recognition and classification.
U.S. Pat. No. 7,639,171 entitled RADAR SYSTEM AND METHOD OF DIGITAL BEAM FORMING describes a radar system that uses non-coherently integrated amplitude spectral profile as the basis for an object detection schema. Detection performance of such amplitude spectrum based NCI-detection schema can be affected by dissimilar interference and coupling effects across receive antenna-array elements. For example, measurement resolution, which is basically determined by the waveform parameters setup, degrades due to interference and coupling effects on the signal spectrum shape. This makes the detection and categorization or classification of multiple near-to-each-other scattering centers difficult. This is particularly true for single targets with multiple or extended scattering centers with similar or different Doppler and reflection characteristics (or Radar Cross Sections, RCS). Typically, the reflected signal from a scattering center with a larger RCS could distort and mask signal from another nearby scattering center with a smaller RCS, which makes object classification difficult. Nearby scattering center detection/distinction is an important step to achieve secondary target discrimination and primary target categorization/classification of various on-road object groups such as: stationary-object, moving-bicyclist, moving-pedestrian, and moving-other-vehicle. The target categorization/classification may also include a determination of relative travel direction such as: longitudinal, lateral or diagonal.
General performance limitations of an amplitude based NCI-detection technique can be improved by proper waveform parameter specification, and narrow beam antenna or antenna-array design. However, this may undesirably increase sensor size, cost, and signal processing complexity. That is, these factors are trade-offs for high resolution radar performance which impose restrictions on any arbitrary radar systems design. That means, a radar system configured with only an amplitude spectrum based NCI-detection technique has limited capability of object discrimination and categorization. An example of such a system is described in U.S. patent application Ser. No. 14/491,192 entitled RADAR SYSTEM WITH PHASE BASED MULTI-TARGET DETECTION and filed 19 Sep. 2014 by the same inventor of the system described herein. That disclosure describes a local phase-spectrum evaluation technique for automotive radars in order to improve performance limitation of near targets detection and discrimination of the detection schema using amplitude spectrum peak detection and evaluation technique. Note that object categorization/classification is the process of dividing detected objects into groups of entities whose parameters are in some way similar to each other. For example, a slowly moving pedestrian or a bicyclist can be categorized together and distinguished from a moving other-vehicle or a stationary on-road object.